Investigation of Neural Correlates of head and facial movement using fNIRS

The neuroimaging method known as functional near-infrared spectroscopy (fNIRS) uses optical absorption to monitor changes in blood oxygenation levels in the brain. This approach is frequently utilized in neuroscience studies to examine the hemodynamics of the brain during various cognitive activities. The interference, noise, and artefacts from many sources create an important challenge in the processing of fNIRS data. The significance of generally consistent body movement on the variability of fNIRS data is still unknown, despite the fact that earlier research have focused on identifying and removing these artefacts. The focus of this research work is to analyze the link between distinct brain areas using a graph theory-based methodology that incorporates both anatomical and functional aspects. Graph reliability and stability analysis have been done with correlations analyses which revealed a considerable increase in the dependability of brain functional connectivity. Among the graph network metrics, path length shows 95% variation while other values were within the related activity area.